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https://issues.apache.org/jira/browse/SPARK-25994?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16856827#comment-16856827
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Ruben Berenguel commented on SPARK-25994:
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Hi [~mju] I'd like to lend a hand if you feel like it (I've been following
on-and-off the discussions and SPIPs for this, and currently use GraphFrames).
Wouldn't mind helping with Python APIs (I'm somewhat familiar with the Python
APIs and a bit of the internals, even if I'm not a frequent user of PySpark)
> SPIP: Property Graphs, Cypher Queries, and Algorithms
> -----------------------------------------------------
>
> Key: SPARK-25994
> URL: https://issues.apache.org/jira/browse/SPARK-25994
> Project: Spark
> Issue Type: Epic
> Components: Graph
> Affects Versions: 3.0.0
> Reporter: Xiangrui Meng
> Assignee: Martin Junghanns
> Priority: Major
> Labels: SPIP
>
> Copied from the SPIP doc:
> {quote}
> GraphX was one of the foundational pillars of the Spark project, and is the
> current graph component. This reflects the importance of the graphs data
> model, which naturally pairs with an important class of analytic function,
> the network or graph algorithm.
> However, GraphX is not actively maintained. It is based on RDDs, and cannot
> exploit Spark 2’s Catalyst query engine. GraphX is only available to Scala
> users.
> GraphFrames is a Spark package, which implements DataFrame-based graph
> algorithms, and also incorporates simple graph pattern matching with fixed
> length patterns (called “motifs”). GraphFrames is based on DataFrames, but
> has a semantically weak graph data model (based on untyped edges and
> vertices). The motif pattern matching facility is very limited by comparison
> with the well-established Cypher language.
> The Property Graph data model has become quite widespread in recent years,
> and is the primary focus of commercial graph data management and of graph
> data research, both for on-premises and cloud data management. Many users of
> transactional graph databases also wish to work with immutable graphs in
> Spark.
> The idea is to define a Cypher-compatible Property Graph type based on
> DataFrames; to replace GraphFrames querying with Cypher; to reimplement
> GraphX/GraphFrames algos on the PropertyGraph type.
> To achieve this goal, a core subset of Cypher for Apache Spark (CAPS),
> reusing existing proven designs and code, will be employed in Spark 3.0. This
> graph query processor, like CAPS, will overlay and drive the SparkSQL
> Catalyst query engine, using the CAPS graph query planner.
> {quote}
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